Machine learning discriminates voice tremor in essential tremor and dysphonia

Abstract

Patients with essential tremor and adductor-type spasmodic dysphonia may manifest a prominent voice tremor. The diagnosis of voice tremor is currently based on perceptual and qualitative analysis. We have recently demonstrated in two independent studies that advanced voice analysis with machine learning objectively discriminates normal voices from those recorded from patients with essential tremor and dysphonia. The aim of this study is to achieve a direct and objective discrimination between voice samples recoded from patients with essential tremor and dysphonia both manifesting voice tremor.